According to the ‘2025 McKinsey State of AI’ survey, 88% of organizations have an AI adoption strategy for at least one business function. However, few have successfully scaled those initiatives across the organization.

The report further reveals:

From recommendation engines to automated pricing dashboards, AI-powered tools have become common in retail. But agentic commerce is shifting the landscape again. AI agents are now doing tasks for shoppers and retailers, like helping them find products, making purchases, and handling post-purchase tasks. 

For years, Integrated Evidence Planning (IEP) has carried a paradox at its core. It is one of the most strategic levers in life sciences, yet the way it has been executed often feels operational, fragmented, and reactive. Teams build structured plans, populate spreadsheets, and align across functions with rigor and expertise. And yet, when a pivotal HTA decision challenges comparator choice, or when a payer questions endpoint relevance, the same thought resurfaces - we could have seen this coming.  

Cloud cost optimization almost always starts strong. 

Enterprises launch FinOps initiatives. They renegotiate contracts with Cloud Service Providers, clean up unused resources, and roll out new cost dashboards. Early wins follow quickly. For the first 60 to 90 days, savings look real and measurable. 

Then the curve turns. By month four, optimization slows. By month six, cloud spend is back on its original trajectory, or worse. This pattern isn’t accidental. 
 
It’s structural.